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At least 253 records · Page 14

Lewis Acid Site Engineering in Chromite Spinels Orchestrated Surface Reconstruction and Surpasses RuO 2 in Oxygen Evolution

Atomic-scale engineering of chromite spinels featuring redox-active tetrahedral A-sites and strong Cr–O covalency offers a promising route to superior platinum-group-metal-free oxygen evolution reaction (OER) catalysts. However, comprehensive studies addressing how cation substitution influences surface chemistry and governs OER activity and durability in chromite spinels remain limited. Here, in this work, a systematic investigation of the multicationic chromite series Ni x Fe y Cr 3−x−y O 4 is presented, identifying composition-dependent Lewis acidity as a descriptor of superior OER performance. It is further demonstrated that tuning surface acidity directly controls dynamic reconstruction processes and lattice-oxygen participation during spinel-based electrocatalysis. Following activation, the optimized Ni 0.8 Fe 0.3 Cr 1.9 O 4 catalyst delivers a current density of 10 mA cm −2 at an overpotential of 235 mV, surpassing RuO 2 , with excellent long-term stability. Integrating microscopic and spectroscopic analysis with operando impedance spectroscopy, it shows that activation generates an oxyhydroxide overlayer and reveals a previously unrecognized link between surface Lewis acidity and the growth kinetics and activity of these shells. Density functional theory calculations indicate that Fe incorporation at octahedral sites raises the O 2p-band center and lowers oxygen-vacancy formation energy, promoting lattice-oxygen activation and triggering reconstruction, yielding enhanced OER. This work integrates cation-driven surface-acidity modulation, acidity-governed reconstruction, and OER activity enhancement into a unified predictive framework for designing earth-abundant spinel-based catalysts.

operando impedance spectroscopy↗

Divertor heat load estimates on NSTX and DIII-D using new and open-source 2D inversion analysis code

A thermography inversion algorithm has been developed in the open-source Python-based computer code, HYPERION, to calculate the heat flux incident on plasma-facing components (PFCs) in axisymmetric tokamaks. The chosen mesh size at the surface significantly affects the calculated transient heat flux results. The calculated transient heat flux will exceed the real value when the mesh size tends to zero but will underestimate the real value when the mesh size is large. A criterion for determining the appropriate mesh size for the transient heat flux calculation will be discussed. The numerical scheme for HYPERION uses a 2D fully implicit finite-difference approach, allowing temperature-dependent thermal properties of PFC materials. The inversion algorithm is benchmarked against established heat flux calculation codes, TACO and THEODOR, based on thermography data from NSTX and DIII-D respectively. The primary benefits of HYPERION compared to TACO and THEODOR are that it is open-source and it allows for the optimization of mesh thickness along the substrate. The algorithm also accounts for the thermal properties of thin surface layers that characteristically form on PFCs due to plasma-material interactions. The agreement between HYPERION and THEODOR is excellent, as the percent difference between the codes is ~5% on average in the case of the DIII-D data for moderate to high heat flux. Verification tests with TACO show slightly higher average percent differences of 8% and 12%. In using HYPERION to study filaments in heat flux, the initial results indicate that small ELMs filaments significantly broaden the divertor heat flux, and decrease divertor peak flux. Compared to the inter-ELM, the small ELM filaments decrease the divertor peak surface temperature. With intermittent divertor filaments, the divertor heat flux width is comparable with that found in L-mode.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Modeling powder spreadability in powder-based processes using the discrete element method

Powder-bed fusion (PBF) processes refer to a subset of Additive Manufacturing (AM) techniques where powder is spread on the build-plate before melting (by a laser or electron beam). While PBF processes are attractive due to their ability for realizing complex structures that are either difficult or impossible to create through conventional means, the parts fabricated with these techniques can exhibit defects such as pores, inclusions, and excessive surface roughness. To minimize these defects, much research has been dedicated towards process maturation by optimizing laser or electron beam parameters. However, these developmental efforts typically do not address the recoating process where achieving dense and uniform layers of powder is a necessity for ensuring process repeatability and part quality. While the recoating process can be studied through experimentation, the dynamics of particle movement are difficult to analyze experimentally. Therefore, here, in this study, powder spreading in PBF was simulated through the Discrete Element Method (DEM) to elucidate the mechanisms that control powder-bed quality. Utilizing the Buckingham Pi theorem, a dimensionless metric referred to as the spreading index is developed that combines powder-bed density, roughness, and particle size to assess the quality of powder layers. The formulated spreading index is then related to several dimensionless quantities that provide insight into the mechanisms dominating powder spreading in PBF. The DEM simulations conducted in this work focused on the scenario where powder is spread onto an existing powder bed and revealed that a reduction in the recoating velocity causes an increase in the spreading index while little to no impact on the spreading index was observed when varying layer thickness from 30 μm to 75 μm.Particle size effects on the powder-bed quality were also investigated.

36 MATERIALS SCIENCE↗

Photocatalytic Ammonia Synthesis using Fe-Based MOFs: The Role of Ligand Functionalization

Photocatalytic ammonia (NH 3 ) synthesis offers a carbon-neutral alternative to the Haber−Bosch process, which generates 42 million metric tons of CO 2 equivalent emissions annually. However, solar-to-ammonia conversion with contemporary photocatalysts remains far from practical requirements, and understanding the limiting factors in systems with well-defined active sites is crucial. Here, we show how the μ 3 -oxo-centered trinuclear Fe cluster in MIL-101(Fe) functions as the catalytic motif for N 2 -to-NH 3 conversion through combined experimental and computational investigations. Comparative studies with a molecular analogue demonstrate that the cluster is stabilized within the MOF framework, sustaining redox cycling and maintaining high catalytic activity. We systematically functionalized the dicarboxylate ligands of MIL-101(Fe) with −NH 2 , −Br, −NO 2 , −F, and −CF 3 to probe how ligand chemistry modulates Fe electron density, N 2 adsorption capacity, and proton availability, correlating these properties with catalytic performance using spectroscopic and surface characterization techniques alongside timeresolved infrared to assess excited-state lifetimes. F-functionalization optimally balances N 2 activation, proton availability at Fe active sites, and excited-state lifetimes, boosting NH 3 production by ∼ 60% relative to unmodified MIL-101(Fe). This study of ligandfunctionalized MIL-101(Fe) MOFs uncovers the underlying structure-activity relationships and advances design principles for solardriven NH 3 synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Materials descriptors for advanced water dissociation catalysts in bipolar membranes

The voltage penalty driving water dissociation (WD) at high current density is a major obstacle in the commercialization of bipolar membrane (BPM) technology for energy devices. Here, in this study, we show that three materials descriptors, that is, electrical conductivity, microscopic surface area and (nominal) surface-hydroxyl coverage, effectively control the kinetics of WD in BPMs. Using these descriptors and optimizing mass loading, we design new earth-abundant WD catalysts based on nanoparticle SnO 2 synthesized at low temperature with high conductivity and hydroxyl coverage. These catalysts exhibit exceptional performance in a BPM electrolyser with low WD overvoltage (η wd ) of 100 ± 20 mV at 1.0 A cm -2 . The new catalyst works equivalently well with hydrocarbon proton-exchange layers as it does with fluorocarbon-based Nafion, thus providing pathways to commercializing advanced BPMs for a broad array of electrolysis, fuel-cell and electrodialys is applications.

Sasmal, Sayantan↗

Antimony Chloride Treatments of CdTe-Based Solar Cells

Development of a new SbCl3-based solution treatment for chloride activation of CdTe-based solar cells is described. Activation was confirmed with CdSeTe:Sb devices exhibiting VOC > 550 mV and JSC > 25 mAcm-2. Treatment optimization showed strong effects of annealing time and temperature on cell properties. Material characterization indicated surface conversion of CdSeTe to CdCl2 and Sb2Te3 with SbCl3 treatment. However, no reaction products were formed with treatment under inert conditions, which was coupled with poor device performance. Drying the SbCl3 films at controlled humidity conditions confirmed that exposure to high relative humidity is critical for CdSeTe activation, through hydrolysis of SbCl3. Mechanistic details of SbCl3 speciation during hydrolysis and annealing to activate CdSeTe are discussed.

14 SOLAR ENERGY↗

Exergetic design and analysis of a freeze-out heat exchanger for helium purification

The freeze-out purification process is very effective in removing moisture contamination and can be utilised for purification of helium gas in cryogenic applications. A process model for a freeze-out helium purifier (up to 30 g/s of contaminated helium at 10 ppmv) with a coiled finned-tube heat exchanger is developed. Furthermore, an extensive 1st and 2nd law (exergy) analysis is carried out and the exergetically optimal heat exchanger configuration (diameter and number of flow passes) for a given heat exchanger surface area ranging from 42.5 m 2 to 57.5 m 2 are found.

cryogenics↗

Examining Graphite Degradation in Molten Salt Environments: A Chemical, Physical, and Material Analysis

Molten-salt reactors (MSRs) are Generation IV nuclear reactors that use liquid salt as a coolant and/or fuel. In several MSR designs, graphite serves as a moderator and/or reflector. However, due to limited experimental data and operational experience, our understanding of graphite behavior in molten salt environments remains incomplete. This report aims to identify the degradation mechanisms of nuclear graphite in MSRs, detail the mechanisms of each factor, and provide an initial assessment of their impact on the structural integrity of graphite components. This assessment is based on an extensive literature review and insights from subject matter experts. Furthermore, given the limited data, a modeling strategy using existing Grizzly software is proposed for a more thorough analysis where appropriate. Additionally, it presents mitigation strategies where applicable. The report covers physical degradation mechanisms such as infiltration, erosion, and abrasion, as well as chemical degradation mechanisms including fluorination, intercalation, corrosion, and oxidation. Molten salt can infiltrate the porous structure of graphite, leading to several detrimental effects. Entrapment of fissile products within the graphite pores can cause radiation damage and could pose challenges in the handling and disposal of contaminated components. The differential thermal expansion between the infiltrated salt and graphite, along with internal stress from pressurized molten salt and volumetric heating, can compromise the structural integrity of graphite. To mitigate these effects, employing ultra-fine graphite grades and applying sealants and coatings are effective strategies. A computational model based on coupled solid mechanics and heat transfer phenomena could be used to predict the internal stresses using Grizzly software. In pebble-bed MSRs, graphite fuel pebbles can cause abrasion against reactor components due to friction and wear. The severity of wear is influenced by various factors such as temperature, environment, and the presence of lubricants. Tribological studies reveal that higher temperatures and molten salt environments, such as FLiBe, significantly reduce wear rates compared to dry conditions. Additionally, the chemical composition of the salt can further optimize graphite's tribological performance. Long-term wear effects can be modeled by incorporating surface defects into the geometry and predict stresses under thermal and radiation effects using Grizzly software. Chemical degradation of graphite in a molten salt environment can occur through fluorination and intercalation. Fluorination can occur via replacement of hydrogen or oxygen atoms, or at the active sites, but does not cause structural degradation. Intercalation, on the other hand, can lead to exfoliation, where layers of graphite separate and peel away, damaging the graphite. Protective coatings can enhance graphite's resistance to intercalation. Graphite generally exhibits good chemical stability in molten salt environments, though it can corrode under specific conditions, particularly in the presence of impurities or oxidants. Studies have shown that protective coatings, such as plasma-sprayed partially stabilized zirconia (PSZ), can effectively prevent such degradation. Corrosion behavior varies significantly with different graphite grades and coating applications, underscoring the need for detailed studies on uncoated and coated graphite to understand and mitigate corrosion mechanisms in MSRs. Research indicates that the presence of oxidants and impurities can accelerate graphite degradation in molten salts, making it essential to explore acceptable impurity limits. Oxidation is another critical degradation mechanism, leading to weight loss and structural damage due to the formation of CO and CO 2 from the reaction of carbon atoms with oxygen. This process creates new porosity and compromises graphite's integrity. While extensive research on graphite oxidation has been conducted for gas-cooled reactors, studies specific to MSRs are limited. Findings from the coal industry suggest that molten alkali metal salts can significantly accelerate graphite oxidation, a hypothesis worth exploring for fluoride salts in MSRs. Understanding oxidation behavior in MSRs is vital for developing protective measures. The analysis of post-irradiated graphite from the MSRE experiment demonstrated exceptional chemical compatibility with molten fluoride salt, suggesting that the extent of chemical attack on graphite largely depends on the salt's infiltration capability. Therefore, the use of ultra-fine grade graphite could help mitigate chemical degradation effects. Existing oxidation modeling capabilities in Grizzly, which use reaction-diffusion equations to model graphite-air interactions, could be adapted to simulate the chemical degradation effects of graphite in molten salt environments.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Probing Surface Hydration and Isotope Exchange Kinetics in Proton-Conducting Ceramics Using DRIFTS and EIS

This internship project investigates how water vapor partial pressure (pH2O) affects surface hydration and H/D isotope-exchange kinetics in BaZr0.4Ce0.4Y0.1Yb0.1O3?d (4411) proton-conducting ceramic electrolytes. Diffuse reflectance infrared Fourier-transform spectroscopy (DRIFTS) is used to monitor surface hydroxyl and deuteroxyl species under controlled humidified atmospheres during gas-switching experiments. These surface kinetic trends are to be correlated with bulk, grain-boundary, and total electrolyte resistance measured by electrochemical impedance spectroscopy (EIS) under matching conditions. The future goals of this study are to clarify the relationship between surface hydration dynamics and proton conduction behavior, improving interpretation of EIS data and guiding the optimization of ceramic electrolytes for energy applications.

08 - HYDROGEN↗

From Powder to Power: Tailored Pre-Milling Strategy that Optimizes Microstructure for Efficient Hydrogen Evolution

The hydrogen evolution reaction (HER) plays a critical role in enabling large-scale electrolytic hydrogen production and advancing future technologies and fuel production. Among non-precious metals, NiMo-based catalysts are particularly attractive due to their capability to promote both water dissociation and hydrogen adsorption in alkaline media. However, conventional NiMo catalysts often suffer from incomplete alloying, particle aggregation, weak metal–support interactions, and surface oxidation, which significantly limit active site utilization, electronic conductivity, and long-term stability. Herein, we report a scalable, solid-state, two-step ball milling strategy for constructing an efficient NiMo/C catalyst for the HER. Pre-milling the metal precursors prior to carbon incorporation promotes efficient solid-state activation, leading to the formation of uniformly alloyed, ultrafine, and defect-rich Ni–Mo nanoparticles with robust metal–carbon interfacial anchoring. Benefiting from this integrated structural design, the optimized NiMo/C catalyst exhibits low overpotentials and Tafel slopes, reduced charge-transfer resistance, and excellent durability under alkaline conditions. Comprehensive structural and surface analysis reveal that the enhanced HER performance can be attributed to the synergistic interplay of homogeneous Ni–Mo alloying, uniform nanoparticle dispersion on a defect-rich carbon scaffold, enhanced accessibility of catalytically active sites, and optimized electronic coupling that stabilizes the catalyst surface. This work highlights the two-step solid-state ball milling strategy as a simple, robust, and scalable route for the preparation of effective and durable non-precious metal HER electrocatalysts, offering practical insights toward large-scale and inexpensive hydrogen production.

Yang, Xiaoxuan [Oak Ridge National Laboratory (ORN↗

Machine-Learned Force Field for Molecular Dynamics Simulations of Nonequilibrium Ammonia Synthesis on Iron Catalysts

Ammonia (NH 3 ) is one of the most important industrial chemicals. The conventional NH 3 synthesis method-the Haber–Bosch process-converts atmospheric nitrogen (N 2 ) into NH 3 using H 2 with an iron (Fe) catalyst. However, this process requires high pressures (100–200 atm) and temperatures (700–800 K) near thermal equilibrium. Recently, Fe-based nanocatalysts have been reported to produce promising NH 3 yields under atmospheric pressures and temperature-modulated nonequilibrium conditions. Understanding the mechanism of nonequilibrium catalysis with programmed temperature variation could help to optimize this fully electrified and less energy-intensive process. Although reactive molecular dynamics (RMD) simulations can be a useful tool to model nonequilibrium catalytic processes, they require the development of accurate force fields (i.e., interatomic potentials). Here, we present a machine-learned (ML) force field within the Deep Potential MD (DPMD) framework, trained using periodic density functional theory (DFT) calculations, to model NH 3 synthesis on Fe catalysts with various surface adsorbates such as *N, *H, *N 2 , *H 2 , *NH, *NH 2 , and *NH 3 . Here, we generated the DFT data from static models of elementary reactions on the most stable (110) surface of body-centered cubic Fe, which then were augmented by data from constant number of particles–volume–temperature (NVT) DFT-MD trajectories at various temperatures. Finally, we utilized the fully optimized ML force field to investigate reaction dynamics at an Fe(110) surface at linearly increasing temperatures using NVT-DPMD simulations. Our simulations indicate that pulsed temperature ramping could prove favorable for NH3 synthesis. For example, we conducted ramping under multiple sets of conditions: (i) from 900 to 1200 K over periods of 0.1–0.3 ns for Fe surfaces precovered with N or NH along with H; and (ii) from 300 to 600 K over 0.1–0.3 ns for Fe surfaces precovered with NH 3 . While our simulations so far are limited to short time scales (very rapid heating), these observations shed light on the mechanism of the high NH 3 synthesis rate achieved in a novel temperature-modulated nonequilibrium catalytic reactor using pulsed heating and cooling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Etching-Chemistry-Driven Ruthenium Doping on Ti 3 C 2 T x MXene for Optimizing Electrochemical Performance

We demonstrate that the etching chemistry used during MXene synthesis from Ti 3 AlC 2 MAX phase significantly influences surface functionalization and structural vacancies, which in turn affect ruthenium (Ru) ion interactions. Using hydrofluoric acid (HF) and ammonium bifluoride (NH 4 HF 2 ) as etchants, we obtained MXene surfaces with distinct functional groups and Ti vacancies that impact Ru ion interactions and electrochemical performance. Both MXene variants (labeled MX(H) and MX(N), respectively) exhibited negative zeta potentials in their pristine state, but upon the addition of Ru the zeta potential for MX(H) reached 12.9 mV while that for MX(N) remained negative at −6.4 mV. This adsorption resulted in a 14.4-fold increase in the specific capacitance of MX(H)/Ru compared to pristine MX(H), whereas MX(N)/Ru exhibited only a 4.4-fold increase over its pristine counterpart. X-ray diffraction analysis identified the formation of ammonium titanium oxide fluoride, (NH 4 ) 3 TiOF 5 , on MX(N), which likely contributed to its reduced Ru adsorption. X-ray photoelectron spectroscopy suggested the presence of Ti vacancies in both MXene variants; however, their behavior toward Ru accommodation differed markedly, with MX(H) showing the most obvious shift in the Ti 2p peak in the XPS survey spectrum, while MX(N) showed the most obvious shift in the C 1s peak. Electron paramagnetic resonance spectroscopy further demonstrated a distinct alteration in the spectral signatures of MX(H) upon Ru addition, in contrast to the negligible changes in MX(N), indicating effective passivation of the Ti defect sites in MX(H) via vacancy-assisted Ru doping. Cyclic voltammetry showed that Ru-incorporated MX(H) nanocomposites exhibit more efficient redox-active sites, as reflected in their higher capacitance values. These findings highlight the pivotal role of MXene surface chemistry in controlling cation adsorption, providing valuable insights for the rational design of high-performance electrodes.

2D surface engineering↗

Breaking the passivation barrier via d-p orbital optimization for stable hydrogen production and sulfion upgrading

The development of energy-efficient hydrogen production technologies represents a critical pathway toward achieving global carbon neutrality objectives. This work provides fundamental insights into overcoming catalyst passivation challenges in sulfide oxidation reaction (SOR)-coupled hydrogen evolution reaction (HER) systems through precise orbital hybridization engineering. Our theoretical simulations reveal that sulfur-passivated ruthenium surfaces can effectively modulate d-p orbital hybridization, significantly reduce d-electron activity while stabilizing long-chain S 8 species and decreasing intermediate adsorption energies. Furthermore, metal carbides/ruthenium heterostructure (MC/Ru, M = V, Mo, W) was designed to achieve simultaneous optimization of both HER (∆G H* = −0.11 eV) and SOR (∆G RDS = 1.51 eV) via work-function-mediated interfacial electron transfer, which effectively tailors surface electronic states. Guided by theoretical predictions, we successfully synthesized a series of metal carbides/ruthenium/nitrogen-doped carbon catalysts based on a solid-phase reaction and designated as MC/Ru@NC (M = V, Mo, W). The optimized VC/Ru@NC catalyst exhibits exceptional performance in a membrane-free two-electrode system, achieving an ultralow cell voltage of 0.76 V at 200 mA cm −2 with outstanding stability over 1600 h, while maintaining 97.5 % Faradaic efficiency for hydrogen production and 73.8 % sulfur recovery efficiency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effects of chemical disorder and spin-orbit coupling on the electronic-structure and Fermi-surface topology of YbSb-based monopnictides

Here, in this work, we study the influence of disorder on the electronic structure of YbSb—a rare-earth monopnictide featuring a simple rocksalt (B1) crystal structure and a well-defined Fermi-surface topology—by employing first-principles density-functional theory. We focus on chemical disorder introduced through Te and Al doping, selected based on their thermodynamic stability in alloyed configurations, to understand how such perturbations modify the electronic states of YbSb. Our results indicate that Te doping predominantly introduces electronlike states at the 𝑋 and 𝐿 points, while Al doping leads to a suppression of holelike states at Γ, effectively driving the system from a semimetallic state to one characterized by very narrow-gap behavior at Γ. This modulation of the Fermi surface, particularly the reduction of central hole pockets at Γ, plays a central role in altering interpocket scattering—a mechanism critical for tuning quantum transport properties, including superconductivity. This disorder-driven modulation of the Fermi surface, particularly the suppression of central hole pockets at Γ, controls interpocket scattering, which is essential for optimizing quantum transport properties, including superconductivity. Our results show that disorder can be effectively used for engineering band topology, thereby tuning quantum related response through a tailored electronic structure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Responsible Adoption of Artificial Intelligence (AI) in Electric Grid Operations

The future of the grid will be powered by AI—or undermined by it. Artificial intelligence is rapidly reshaping grid operations, improving fault detection, forecasting accuracy, and real-time optimization. As AI systems move closer to operational decision loops, however, they introduce new consequence pathways: expanded attack surfaces, model integrity risks, regulatory exposure, and human-automation challenges. This talk presents a consequence-driven framework for deploying AI responsibly in the electric grid. Attendees will gain practical strategies to strengthen resilience, boost reliability, and deploy AI securely — ensuring the grid of the future is not only smarter but safer.

25 - ENERGY STORAGE↗

Data-Driven Modeling and Control of Systems with Plasma-Surface Interactions (Final Technical Report)

This final technical report summarizes the activities and accomplishments in the period from February 2023 thru January 2026. The objective of the proposed research is to investigate the physical mechanisms and processes underlying the formation of structures and patterns in systems with plasma-surface interactions. In the past decades, there have been extensive studies on the interaction of glow discharges, dielectric barrier discharges, and arc discharges with confining or intervening surfaces. The advancement of the understanding of these phenomena is not only of fundamental scientific interest and relevance to the knowledge of the plasma state, but also with profound implications in various technological applications. The research will integrate theoretical, computational, and experimental work within an innovative framework of data assimilation, i.e., optimally combining model predictions with measurements. The scientific merit of this research has three aspects. Firstly, it extends the studies of plasma-surface interactions to systems with insulator surfaces and multi-layer systems, while existing studies are predominantly on electrode surfaces. Secondly, it expects to develop a novel data-driven modeling approach based on data assimilation to enhance the predictive and control capabilities, which could make transformative contributions to basic plasma research. Thirdly, it will shed new light on outstanding problems related to formation of patterns interfacing plasmas. This project also aims to launch an education and outreach initiative at Texas A&M University-Kingsville, a non-R1, minority-serving institution in South Texas. The initiative is structured as a four-tier pyramid. Tier one will be a webinar series for culture and capacity building to inform broader audience in the region about the research fields of plasma science and engineering. Tier two will be the creation and offering of an upper-level undergraduate course on introductory plasma physics, which will help with the recruitment for the upper tiers. On tier three, we will engage and mentor senior design students to conduct work toward the research goal of this project. There will also be a certificate program on general plasma science for undergrad and graduate students, part of which will be lab training at Princeton University. Tier four will be the supervision and mentoring of Ph.D. students. Therefore, this project will systematically expand the talent pipeline, broaden participation from communities historically and geographically underrepresented in DOE SC research portfolio, significantly improve the research and education capacity at the PI’s institution, and contribute to developing a diverse workforce in plasma science and engineering.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

CALPHAD-based Bayesian optimization to accelerate alloy discovery for high-temperature applications

Two crucial properties influencing the performance of high-temperature alloys are coefficient of thermal expansion (CTE) and phase constitution. It is desirable to have alloys with low CTE, which reduces CTE mismatch with the surface oxide and the likelihood of oxide spallation. Reducing the amount of brittle intermetallic phases such as Sigma (σ) enhances alloy ductility and processability. Here, we propose a multi-objective Bayesian Optimization (BO) model to simultaneously minimize CTE (at an operational temperature of 1150 °C) and T σ (temperature when the Sigma phase completely dissolves in the metal matrix), properties which are obtained from high-throughput CALculation of PHAse Diagrams (CALPHAD). The model successfully identifies several alloys with CTE ≤ 2 × 10 –5 /K and T σ ≤ 500 °C by exploring just 7% of the nickel–chromium–cobalt–aluminum–iron (Ni–Cr–Co–Al–Fe) composition space. Such multi-objective alloy design frameworks can be used to inform additive manufacturing experiments and accelerate alloy discovery for high-temperature energy applications.

36 MATERIALS SCIENCE↗

CFD Simulation of the Dosing Behavior within the Atomic Layer Deposition Feeding System

The effective operation of atomic layer deposition (ALD) feeding system is the premise of realizing specific ALD processes. In the present work, a detailed computational fluid dynamics (CFD) model of the feeding system has been developed and validated, which accounts for the roles of ALD valves and manifolds. A numerical simulation of the compressible fluid flow and heat/mass transfer within the feeding system was conducted. The dosing amounts and the spatiotemporal distributions of the precursors can be accurately predicted using the CFD model, as validated by experimental results. Different precursors, operating conditions, and structures of the feeding system were simulated and analyzed to examine the operating flexibility of the feeding system. The simulation results can be adopted as the upstream boundary conditions for simulations of the ALD process in the reaction chamber. The substrate-scale simulation indicates that the effect of the feeding system on the film deposition is highly related to the surface kinetics of ALD. The present work can serve as a guide for the development and optimization of different ALD-based processes via proper operation and even the design of the feeding system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗